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Memory is the retention of information or experiences over time, facilitated through three main processes: encoding, storage, and retrieval. Encoding is the process of inputting information into the memory system. For instance, when listening to a lecture, watching a play, reading a book, or having a conversation, the brain is actively encoding information. This initial stage involves transforming sensory input into a form that can be processed and stored by the brain. Various factors, such as...

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Related Experiment Video

Updated: Nov 21, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

Memory as a Computational Resource.

Ishita Dasgupta¹, Samuel J Gershman²

¹Department of Computer Science, Princeton University, Princeton, NY, USA.

Trends in Cognitive Sciences

|January 17, 2021

Summary

Sophisticated algorithms use memory to avoid redundant computations. This principle applies to cognitive processes like mental arithmetic, imagery, planning, and inference, enabling efficient thinking.

Keywords:

amortization inference memory mental arithmetic mental imagery planning

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Last Updated: Nov 21, 2025

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Area of Science:

Cognitive Science
Computer Science
Computational Neuroscience

Background:

Naive algorithms often lead to excessive redundant computations.
Sophisticated algorithms leverage memory to store and reuse results, enhancing efficiency.
This computational efficiency principle is increasingly recognized in cognitive science.

Purpose of the Study:

To review the application of memory-based computational efficiency in cognitive science.
To explore commonalities in cognitive processes through the lens of computational optimization.
To demonstrate how memory enhances the efficiency of complex cognitive tasks.

Main Methods:

Review of existing literature on computational algorithms and cognitive processes.
Analysis of four distinct cognitive domains: mental arithmetic, mental imagery, planning, and probabilistic inference.
Comparative analysis to identify shared reliance on memory for computational efficiency.

Main Results:

Identified a common reliance on memory across diverse cognitive processes.
Demonstrated that storing and reusing computational results significantly improves efficiency.
Showcased how memory-based strategies mitigate redundant computations in cognition.

Conclusions:

Cognitive processes, despite superficial differences, share a fundamental reliance on memory for efficient computation.
The principles of computational optimization through memory are broadly applicable in understanding the mind.
Harnessing memory is key to efficient cognitive function, mirroring efficient algorithmic design.